International Journal of Obesity (2005) 29, 1464–1470 & 2005 Nature Publishing Group All rights reserved 0307-0565/05 $30.00 www.nature.com/ijo
PAPER High amount of visceral fat mass is associated with multiple metabolic changes in offspring of type 2 diabetic patients U Salmenniemi1, E Ruotsalainen1, M Va¨nttinen1, I Vauhkonen1, J Pihlajama¨ki1, S Kainulainen2, K Punnonen3 and M Laakso1* 1 Department of Medicine, University of Kuopio, Kuopio, Finland; 2Department of Radiology, University of Kuopio, Kuopio, Finland; and 3Department of Clinical Chemistry, University of Kuopio, Kuopio, Finland
OBJECTIVE: To investigate the relative contribution of total body fat mass (TFM) and intra-abdominal fat mass (IAFM) to metabolic consequences of obesity in offspring of type 2 diabetic parents. DESIGN: Cross-sectional study of 129 nondiabetic offspring of diabetic parents (59 men, 70 women, age 35.776.3 y, body mass index 26.274.6 kg/m2). Study subjects were grouped according to TFM (assessed with bioelectrical impedance) and IAFM (assessed with CT). Insulin sensitivity was assessed with the euglycemic hyperinsulinemic clamp, insulin secretion with the intravenous glucose tolerance test and energy expenditure with indirect calorimetry. Furthermore, C-reactive protein (CRP) and adiponectin levels were measured. RESULTS: Insulin resistance, low rates of oxidative and nonoxidative glucose disposal, high rates of lipid oxidation and reduced energy expenditure during hyperinsulinemia were associated with high IAFM, independently of TFM. Adiponectin level was reduced and CRP level increased in subjects with high IAFM. CONCLUSIONS: The metabolic changes relating to obesity are largely attributable to high IAFM, and are present even in normal weight subjects with high IAFM. International Journal of Obesity (2005) 29, 1464–1470. doi:10.1038/sj.ijo.0803041; published online 26 July 2005 Keywords: visceral fat; metabolic syndrome; insulin sensitivity; energy expenditure; cytokines
Introduction Obesity is associated with insulin resistance, metabolic syndrome and type 2 diabetes (T2DM). Susceptibility to complications of obesity is particularly associated with abdominal obesity, and waist circumference has been considered a reliable marker for the metabolic syndrome.1 However, controversy still exists on the relative contribution of visceral abdominal fat and subcutaneous fat to metabolic consequences of obesity.2–8 Previous conflicting findings may partially be due to the heterogeneity of study designs. There are only a few studies where insulin sensitivity has been assessed by the hyperinsulinemic clamp and fat distribution by CT or MRI.2–5,7–9 Furthermore, the number of subjects has been limited (mostly o50 subjects) and study *Correspondence: Dr M Laakso, Department of Medicine, University of Kuopio, Kuopio 70210, Finland. E-mail:
[email protected] Received 28 January 2005; revised 6 June 2005; accepted 13 June 2005; published online 26 July 2005
subjects have differed considerably with respect to gender, age, body weight and glucose tolerance. No previous data are available on substrate oxidation with respect to fat distribution. First-degree relatives of T2DM patients are genetically predisposed to insulin resistance and they are often obese, and therefore they are ideal study subjects when assessing metabolic consequences of obesity. However, there are only few previous studies including a small number of subjects investigating metabolic changes related to visceral obesity in first-degree relatives of T2DM patients.4,10 Therefore, we metabolically characterized 129 nondiabetic offspring of patients with T2DM, and divided these subjects into four different groups according to total fat mass (TFM) and intraabdominal fat mass (IAFM). The primary aim of the study was to investigate the relative contribution of general vs intra-abdominal obesity to metabolic consequences of obesity, particularly on insulin resistance, changes in energy expenditure, substrate oxidation and levels of adipokines.
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Subjects Altogether, 129 offspring of patients with T2DM were included in the present study. The probands were randomly selected from T2DM patients living in the Kuopio University Hospital region. The exclusion criteria for the selection of the subjects were: (1) diabetes mellitus or any other disease that could potentially disturb carbohydrate metabolism; (2) diabetes mellitus in both parents; (3) pregnancy; and (4) age under 25 or over 50 y. The Ethics Committee of the University of Kuopio and the Kuopio University Hospital approved the study protocol. All study subjects gave informed consent.
Study design The studies were conducted on the metabolic ward of the Department of Medicine at the Kuopio University Hospital on three different occasions 1–2 months apart, as previously described in detail.11 On the first visit, blood pressure was measured in a sitting position after a 5-min rest with a mercury sphygmomanometer. Height and weight were measured to the nearest 0.5 cm and 0.1 kg, respectively. Body mass index (BMI) was calculated as weight in kilograms divided by height in meters squared. Waist (at the midpoint between the lateral iliac crest and lowest rib) and hip circumference (at the level of the trochanter major) were measured to the nearest 0.5 cm. Blood samples were drawn for the measurement of plasma glucose, insulin, C-peptide and serum lipids after 12 h fast followed by an oral glucose tolerance test (OGTT). On the second occasion, bioelectric impedance measurement and indirect calorimetry were performed after 12 h fast followed by an intravenous glucose tolerance test (IVGTT) and the hyperinsulinemic euglycemic clamp, respectively. Indirect calorimetry was reperformed during the last 30 min of the euglycemic clamp. On the third occasion, a CT scan for the evaluation of the abdominal fat area and exercise test to determine maximum oxygen uptake were performed.
Metabolic studies In a 2-h OGTT (75 g of glucose) blood samples for plasma glucose and insulin determinations were drawn at 0, 30, 60, 90 and 120 min to evaluate glucose tolerance. Those with normal (NGT) or impaired (IGT) glucose tolerance according to the World Health Organization criteria12 were included in the study. An IVGTT was performed to determine the first phase insulin secretion capacity.13 After baseline blood collection, a bolus of glucose (300 mg/kg in a 50% solution) was given within 30 s into the antecupital vein in order to raise acutely the blood glucose level. Samples for the measurement of blood glucose and plasma insulin were drawn at 5, 0, 2, 4, 6, 8, 10 and 20 min. The degree of insulin sensitivity was evaluated with the euglycemic hyperinsulinemic clamp technique.14 After an
IVGTT, a priming dose of insulin (Actrapid 100 IU/ml, Novo Nordisk, Gentofte, Denmark) was administered during the initial 10 min to raise acutely plasma insulin to the desired level, where it was maintained by a continuous infusion rate of 240 pmol/min/m2 body surface area. Blood glucose was clamped at 5.0 mmol/l for the next 120 min by infusion of 20% glucose at various rates according to blood glucose measurements performed at 5-min intervals. The mean amount of glucose given was calculated for each 20-min interval and the mean value for the last 20-min interval was used as the rates of whole body glucose uptake (WBGU). Samples for insulin and serum free fatty acid (FFA) measurements were drawn at 0 and 120 min. A previous study has shown that an IVGTT prior the euglycemic clamp does not have a significant effect on insulin sensitivity.15 Indirect calorimetry was performed with a computerized flowthrough canopy gas analyzer system (DELTATRACs, TM Datex, Helsinki, Finland). Gas exchange was measured for 30 min in the fasting state (before an IVGTT) and during the last 30 min of the euglycemic clamp. The mean value of the data during the last 20 min was used to calculate glucose and lipid oxidation. Protein oxidation was calculated on the basis of the urinary nonprotein nitrogen excretion rate.16 The fraction of carbohydrate nonoxidation during the euglycemic clamp was estimated by subtracting the carbohydrate oxidation rate from the glucose infusion rate.
Body composition and abdominal obesity Body composition was determined by bioelectrical impedance (RJL Systemss, Detroit, USA, resistance values were within 5% and reactance values within the range of 10% precision of standard) in the supine position after a 12-h fast.17 Abdominal adipose tissue area was evaluated by CT (Siemens Volume Zoom, Germany) at the level of fourth lumbal vertebra. Subcutaneous and intra-abdominal fat (IAF) areas were calculated as described previously.18
Assays and calculations Blood and plasma glucose were measured by the glucose oxidase method (Glucose & Lactate Analyzer 2300 Stat Plus, Yellow Springs Instrument Co., Inc., Ohio, USA). Plasma insulin and C-peptide were determined by radioimmunoassay (Phadeseph Insulin RIA 100, Pharmacia Diagnostics AB, Uppsala, Sweden). Serum lipid and lipoprotein concentrations were determined from fresh serum samples drawn after a 12-h overnight fast. Cholesterol and triglyceride levels from whole serum and from lipoprotein fractions were assayed by automated enzymatic methods (Roche Diagnostics, Mannheim, Germany). Serum FFAs were determined by an enzymatic method from Wako Chemicals GmbH (Neuss, Germany). C-reactive protein (CRP) was determined by Immulite 2000 High Sensitivity CRP assay (DPC, Los Angeles, CA, USA) and adiponectin by the Human Adiponectin ELISA Kit (B-Bridge International Inc., San Jose, CA, International Journal of Obesity
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1466 USA). Nonprotein urinary nitrogen was measured by automated Kjeldahl method.19
Statistical analysis Data analyses were performed with the SPSS 11.0 for windows programs. The results for continuous variables are given as means7s.d. Variables with skewed distribution were logarithmically transformed for statistical analyses. Linear mixed model analysis was applied to test the differences between the groups and to adjust for confounding factors.20 Pedigree membership was included as a random factor and gender as a fixed factor. Correlation between continuous variables was tested using linear regression analysis. The incremental insulin areas under the curve were calculated by the trapezoidal method.
Results Among 129 offspring included in the study, no significant gender differences were found regarding age, BMI or glucose tolerance. Men had higher waist circumference and higher IAFM (assessed with CT) than women despite lower TFM (assessed with bioelectrical impedance). Furthermore, men had higher blood pressure, fasting glucose, total cholesterol and triglycerides, and lower high-density lipoprotein (HDL) cholesterol than women (Table 1). For further statistical analyses, subjects were grouped according to the genderspecific median of IAFM (114.4 and 66.1 cm2 for men and women, respectively) and TFM (19.1 and 23.5 kg, respectively). These cutoff points were used to define the following four subgroups: subjects with low IAFM and TFM, subjects
Table 1
Clinical and laboratory characteristics of the study subjects Offspring of T2DM patients
Number of cases NGT/IGT Age (y) BMI (kg/m2) Waist (cm) Fat mass (kg) Intra-abdominal fat (cm2) Systolic blood pressure (mmHg) Diastolic blood pressure (mmHg) Fasting plasma glucose (mmol/l) 120 min plasma glucose (mmol/l) Fasting plasma insulin (pmol/l) 120 min plasma insulin (pmol/l) Total cholesterol (mmol/l) HDL cholesterol (mmol/l) Total triglycerides (mmol/l)
Men
Women
P-value
59 52/7 34.976.2 26.073.5 93.179.6 20.877.0 125.1767.8 130.6713.9 86.1710.7 5.470.4 6.271.5 48.8726.6 229.17215.8 5.0570.89 1.1470.22 1.3570.70
70 58/12 36.476.4 26.375.4 85.0711.9 25.8710.1 85.0748.5 124.1710.4 81.978.2 5.070.4 6.371.4 45.9719.0 272.87176.7 4.7870.86 1.3770.28 0.9870.49
NS NS NS o0.001 0.002 o0.001 0.006 0.014 o0.001 NS NS NS NS o0.001 o0.001
Data are mean7s.d. NS ¼ not significant; T2DM ¼ type 2 diabetes mellitus; NGT ¼ normal glucose tolerance; IGT ¼ impaired glucose tolerance; HDL ¼ high-density lipoprotein.
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with high IAFM and low TFM, subjects with low IAFM and high TFM and subjects with high IAFM and TFM. In the entire study group, the Pearson correlation coefficient between IAFM and TFM was 0.413 (Po0.001). Among the parameters measuring adiposity and fat distribution, TFM had the highest correlation with subcutaneous fat mass (r ¼ 0.875, Po0.001), and IAFM with waist circumference (r ¼ 0.709, Po0.001). Within each subgroup the correlation between IAFM and TFM was no longer statistically significant, whereas the correlation between subcutaneous and TFM was statistically significant (r ¼ 0.675, Po0.001 in the group of low IAFM and low TFM; r ¼ 0.888, Po0.001 in the group of low IAFM and high TFM; r ¼ 0.610, P ¼ 0.007 in the group of high IAFM and low TFM; r ¼ 0.848, Po0.001 in the group of high IAFM and high TFM). The correlation between IAFM and waist circumference was significant in all groups (r ¼ 0.710, Po0.001 in the group of low IAFM and low TFM; r ¼ 0.587, P ¼ 0.010 in the group of high IAFM and low TFM; r ¼ 0.534, Po0.001 in the group of high IAFM and TFM), with the exception of subjects with low IAFM and high TFM (r ¼ 0.066, P ¼ 0.796). Table 2 shows clinical and metabolic characteristics of the subgroups. Subjects with a similar amount of IAFM had similar metabolic characteristics, independently of adiposity. High amount of IAFM was associated with adverse metabolic changes, such as high diastolic blood pressure, high fasting and 2-h insulin, 2-h glucose, triglycerides and low HDL cholesterol. Similar differences between the groups according to the amount of IAFM were observed in substrate oxidation and energy expenditure during the hyperinsulinemic clamp. The rates of WBGU during the clamp was higher in subjects with low IAFM (63.99717.00 and 63.52715.48 mmol/kg/min in subjects with low and high TFM, respectively) than in subjects with high IAFM (52.77712.32 and 47.767 14.41 mmol/kg/min in subjects with low and high TFM, respectively, Figure 1a). The differences were attributable to both oxidative and nonoxidative glucose disposal (22.4374.49 and 41.50715.80 mmol/kg/min in subjects with low IAFM and low TFM, respectively; 20.0975.25 and 34.9678.31 mmol/kg/min in subjects with high IAFM and low TFM, respectively; 24.3874.61 and 39.27713.34 mmol/ kg/min in subjects with low IAFM and high TFM, respectively; 18.2074.75 and 29.98711.29 mmol/kg/min in subjects with high IAFM and high TFM, respectively, Figure 1b and c). However, the differences between subjects with low IAFM and low TFM, and subjects with high IAFM but low TFM, did not reach statistical significance (P ¼ 0.053 for oxidative and P ¼ 0.098 for nonoxidative glucose disposal). Energy expenditure was similar in subjects with high IAFM, independently of TFM (20.7771.53 and 20.877 1.62 cal/kg LBM/min in subjects with low TFM and high TFM, respectively), but significantly lower than in subjects with low IAFM (21.5471.86 and 22.9172.64 cal/kg LBM/ min in subjects with low TFM and high TFM, respectively, Figure 2a). No statistically significant differences were
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1467 Table 2
Clinical and laboratory characteristics of the study subjects grouped according to the amount of total fat mass and intra-abdominal fat mass (IAFM) Low fat mass
Number of cases Men/women Age (y) NGT/IGT BMI (kg/m2) Waist (cm) Fat mass (kg) IAF (cm2) Systolic BP (mmHg) Diastolic BP (mmHg) Fasting glucose (mmol/l) 120 min glucose (mmol/l) Fasting plasma insulin (pmol/l) 120 min plasma insulin (pmol/l) Total cholesterol (mmol/l) HDL cholesterol (mmol/l) Total triglycerides (mmol/l)
High fat mass
Low IAF I
High IAF II
Low IAF III
High IAF IV
P-valuea
46 21/25 34.676.45 5 23.072.24 79.977.13 16.673.7 59.6724.2 126.7712.5 81.479.8 5.0770.35 6.1271.31 36.4712.7 182.87125.8 4.7170.75 1.3870.26 0.9670.52
18 8/10 37.276.98 2 24.571.92*** 87.5876.70*** 18.972.0 126.7748.6 129.4712.0 84.579.5 5.1870.38 5.8071.39 50.3721.3*** 248.87172.2 4.8971.01 1.1470.27*** 1.2870.79
18 8/10 32.6174.69* 0 26.673.8* 88.3676.06 26.076.3 63.9719.7 124.978.4 81.677.5 5.0670.31 5.6771.23 40.1714.8 184.77129.7 4.8470.95 1.3770.24* 1.0370.69
47 22/25 37.4075.96** 12 29.7174.85** 97.82711.41** 31.179.2 152.3760.7 127.4714.0 86.879.6** 5.2170.48 6.7871.49** 59.4727.2** 349.07240.8** 5.1270.90 1.1570.25** 1.3370.56**
NS 0.015 0.042 o0.001 o0.001 o0.001 o0.001 NS 0.025 NS 0.008 o0.001 o0.001 NS o0.001 0.005
Group medians have been used as cutoff points separately for men and women. IAF ¼ intra-abdominal fat; NGT ¼ normal glucose tolerance; IGT ¼ impaired glucose tolerance; BP ¼ blood pressure; HDL ¼ high density lipoprotein. Data are mean7s.d. aAdjusted for gender and familiality using mixed linear model. *Pr0.05 for pairwise comparison between groups II and III. **Pr0.05 for pairwise comparison between groups III and IV. ***Pr0.05 for pairwise comparison between groups I and II.
observed in RQ between the groups in the fasting state (0.8370.05 for subjects with low IAFM and TFM; 0.8270.04 for subjects with high IAFM but low TFM; 0.8370.04 for subjects with low IAFM but high TFM; 0.8270.05 for subjects with high IAFM and TFM). Lipid oxidation during the clamp was highest in subjects with high IAFM and TFM (0.3270.29 mg/kg/min for subjects with low IAFM and TFM; 0.3770.30 mg/kg/min for subjects with high IAFM but low TFM; 0.3170.20 mg/kg/ min for subjects with low IAFM but high TFM; 0.5670.31 mg/kg/min for subjects with high IAFM and TFM, Figure 2c). That was also seen in respiratory quotient, which was lowest among subjects with high IAFM and TFM (0.8970.04, Figure 2b). No significant differences were observed in FFA levels in fasting or during the clamp (data not shown). First-phase insulin secretion in an IVGTT was highest in subjects with high IAFM mass but low TFM (3005.77 2074.7 pmol/l/min), reflecting compensatory hyperinsulinemia to insulin resistance. However, this compensation was not observed in subjects with high IAFM and high TFM (1971.871198.9 pmol/l/min) whose insulin level paralleled those of subjects with low IAFM and low TFM (1503.67998.9 pmol/l/min) and subjects with low IAFM and high TFM (1908.671378.5 pmol/l/min, Figure 3a). There was a clear association between IAFM and adiponectin level independently of TFM (11.1174.51 for subjects with low IAFM and low TFM; 8.1272.77 for subjects with high IAFM and low TFM; 11.5474.77 for subjects with low IAFM and high TFM and 8.3573.05 mg/ml for subjects with high IAFM and high TFM, Figure 3b). Similar findings were observed with respect to CRP level, although only the
difference between subjects with low IAFM and high TFM, and subjects with high IAFM and TFM reached statistical significance (1.3571.94 for subjects with low IAFM and TFM; 2.5273.51 for subjects with high IAFM and low TFM; 1.2871.20 for subjects with low IAFM and high TFM; 2.8373.22 pg/ml for subjects with high IAFM and TFM, Figure 3c). We also analyzed our data including IAFM and TFM as continuous variables in regression models, because subdividing study subjects into four different groups may reduce the power of statistical analyses. In univariate linear regression analysis, only IAFM, but not TFM, was significantly associated with low rates of WBGU (Po0.001), low energy expenditure (Po0.001) and high lipid oxidation during the clamp (Po0.001), low adiponectin level (P ¼ 0.002) and high CRP (Po0.001). When both TFM and IAFM were included as independent variables in multiple linear regression models, all P-values remained practically unchanged, verifying that IAFM was associated with adverse changes in metabolic variables independently of TFM.
Discussion The most important findings of our study were that in a large sample of offspring of T2D parents, subjects with high IAFM had hypoadiponectinemia and high CRP level, and during hyperinsulinemia, low rates of whole body, oxidative and nonoxidative glucose uptake, low energy expenditure and high rates of lipid oxidation. As previous studies have not included indirect calorimetry, our findings related to intracellular glucose metabolism, lipid oxidation and energy metabolism are novel. International Journal of Obesity
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90 80 70 60 50 40 30 20 10 0
P < 0.001 ∗
a
∗∗∗
30
Energy expenditure during the clamp (cal/kg LBM/min)
Whole body glucose uptake (µmol/kg LBM/min)
a
∗
25
P < 0.001 ∗∗
∗ ∗∗
P < 0.001
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20 15 10 5
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b 0.98 RQ during the clamp
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Glucose oxidation during the clamp (µmol/mg LBM/min)
0
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25 20 15 10 5
0.90 0.88
0.84
P = 0.001 ∗
60
c
50 40 30 20 10 low low
low high
high low
high total fat mas high IAF mass
Figure 1 Rates of WBGU (a), oxidative (b) and nonoxidative (c) glucose disposal during the clamp in offspring of T2DM according to the amount of TFM and IAFM. P-values are adjusted for gender and familiality. *Pr0.05, **Pr0.01, ***Pr0.001 in pairwise comparison.
Abdominal obesity is a central feature of the metabolic syndrome and closely associated with insulin resistance.21 In most previous studies, and also in the present study, insulin resistance has been associated more strongly with IAFM than with subcutaneous fat mass, although also opposite findings, suggesting a stronger relationship between subcutaneous fat mass and insulin resistance, have been published.7,8 In addition, our results that subjects with low IAFM but high TFM had similar metabolic profile as did subjects with low IAFM and low TFM, gives further evidence that metabolic consequences of obesity are largely attributable to high IAFM. In fact, the subgroup having high IAFM but low TFM fulfils the criteria for ‘metabolically obese normal weight subjects’, introduced already over 20 y ago.22 IAFM was associated with all components of the metabolic syndrome, except for systolic blood pressure that did not International Journal of Obesity
0.92
Lipid oxidation during the clamp (mg/kg/min)
Nonoxidative glucose disposal during the clamp (µmol/kg LBM/min)
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c
0.96
1 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0
low low
low high
high low
high total fat mas high IAF mass
Figure 2 Energy expenditure (a), respiratory quotient (b) and lipid oxidation (c) during the clamp in offspring of T2DM according to the amount of TFM and IAFM. P-values are adjusted for gender and familiality. *Pr0.05, **Pr0.01, ***Pr0.001 in pairwise comparison.
differ significantly between the groups. This indicates that high blood pressure has different etiology compared to other components of the syndrome. Of importance is also our finding that subjects with low IAFM and high TFM and subjects with high IAFM and low TFM had similar waist circumference, although completely different metabolic profile. Therefore, although waist circumference can be generally used as a measure for intra-abdominal obesity in clinical practice, this is not applicable to all subjects. Thus, the clinical significance of abdominal obesity should be evaluated in relation to other characteristics of the metabolic syndrome. The most significant difference between the groups having high IAFM was that the first phase insulin secretion in an
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1469 First-phase insulin secretion over basal (Pmol/l*min)
a
6000
∗ ∗∗
P < 0.001
5000 4000 3000 2000 1000 0
Adlponectin (µg/ml)
b
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P = 0.001 ∗∗
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∗
6 5 4 3 2 1 0
low low
low high
high low
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Figure 3 First-phase insulin secretion (a) and level of adiponectin (b) and CRP (c) in offspring of T2DM according to the amount of TFM and IAFM. Pvalues are adjusted for gender and familiality. *Pr0.05, **Pr0.01, ***Pr0.001 in pairwise comparison.
IVGTT was clearly impaired in subjects with high TFM, and that compensatory hyperinsulinemia observed in subjects with high IAFM and low TFM was missing. This is partly due to a high number of subjects with IGT in this group, but it may also reflect the accumulation of lipids in b-cells with weight gain, which might lead to lipotoxicity and reduced insulin secretion capacity.23 Similarly, subjects with high IAFM and TFM differed from other subjects with respect to substrate oxidation during hyperinsulinemia. These subjects had the highest rate of lipid oxidation reflecting ‘metabolic inflexibility’ associated with insulin resistance.24 Decreased lipid oxidation during postabsorptive phase may result in lipid accumulation in skeletal muscle, which impairs insulin signalling through substrate competition.24 High IAFM was also associated with low energy expenditure during hyperinsulinemia. This novel finding suggests that viscerally obese subjects are likely to be more prone to weight gain than
subjects with low IAFM. One potential explanation is lower dietary-induced thermogenesis, secondary to impaired sympathetic stimulation in visceral obesity.25 While our data clearly show that high IAFM plays a central role in the pathogenesis of obesity-related disorders, including insulin resistance, it is impossible to conclude which one of these two, IAFM or insulin resistance, is the primary metabolic abnormality on the basis of a cross-sectional study. Insulin resistance and visceral obesity are tightly linked through increased delivery of FFAs from expanded visceral depots to liver resulting in increased gluconeogenesis, verylow-density lipoprotein particle production and hyperinsulinemia.26 However, some recent data on lipolytic activity and FFA availability of different adipose depots demonstrate that the relative amount of portal vein FFAs derived from visceral fat is much less than that derived from lipolysis of subcutaneous fat.27,28 Although FFAs are elevated when IAFM increases, only approximately 5 and 20% of portal vein FFAs originates from visceral fat in lean and obese subjects, respectively.27,28 Other potential site-specific differences in adipocyte biology making visceral obesity more harmful are differences in cell size, production of adipokines, and hormonal and neuronal responsiveness.29 Our findings are in accordance with the hypothesis that hyperinsulinemia, lipid abnormalities (high triglycerides and low HDL cholesterol) and changes in adipokine and cytokine levels (low adiponectin and high CRP) are related to an increase in IAFM. In conclusion, our study demonstrates the impact of IAF on metabolic consequences associated with obesity in offspring of T2DM patients. Adverse metabolic changes were observed even in normal weight subjects with high IAFM. Furthermore, high IAFM was associated with low energy expenditure during hyperinsulinemia, suggesting susceptibility to weight gain and thereby further deterioration of metabolism in viscerally obese subjects. Finally, our data suggest that overweight subjects with low visceral fat mass are relatively free of metabolic complications of obesity.
Acknowledgements This study was partly supported by grants to ML from the Academy of Finland (project 77299), the Diabetes Research Foundation, the Kuopio University Hospital (EVO Grant no. 5194) and the European Union (QLG1-CT-1999-00674).
References 1 Carr DB, Utzschneider KM, Hull RL, Kodama K, Retzlaff BM, Brunzell JD, Shofer JB, Fish BE, Knopp RH, Kahn SE. Intraabdominal fat is a major determinant of the National Cholesterol Education Program Adult Treatment Panel III criteria for the metabolic syndrome. Diabetes 2004; 53: 2087–2094. 2 Brochu M, Starling RD, Tchernof A, Matthews DE, Garcia-Rubi E, Poehlman ET. Visceral adipose tissue is an independent correlate of glucose disposal in older obese postmenopausal women. J Clin Endocrinol Metab 2000; 85: 2378–2384.
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1470 3 Ross R, Aru J, Freeman J, Hudson R, Janssen I. Abdominal adiposity and insulin resistance in obese men. Am J Physiol Endocrinol Metab 2002; 282: E657–E663. 4 Nyholm B, Nielsen MF, Kristensen K, Nielsen S, Ostergard T, Pedersen SB, Christiansen T, Richelsen B, Jensen MD, Schmitz O. Evidence of increased visceral obesity and reduced physical fitness in healthy insulin-resistant first-degree relatives of type 2 diabetic patients. Eur J Endocrinol 2004; 150: 207–214. 5 Gastaldelli A, Miyazaki Y, Pettiti M, Matsuda M, Mahankali S, Santini E, DeFronzo RA, Ferrannini E. Metabolic effects of visceral fat accumulation in type 2 diabetes. J Clin Endocrinol Metab 2002; 87: 5098–5103. 6 Tulloch-Reid MK, Hanson RL, Sebring NG, Reynolds JC, Premkumar A, Genovese DJ, Sumner AE. Both subcutaneous and visceral adipose tissue correlate highly with insulin resistance in african americans. Obes Res 2004; 12: 1352–1359. 7 Kelley DE, Thaete FL, Troost F, Huwe T, Goodpaster BH. Subdivisions of subcutaneous abdominal adipose tissue and insulin resistance. Am J Physiol Endocrinol Metab 2000; 278: E941–E948. 8 Abate N, Garg A, Peshock RM, Stray-Gundersen J, Grundy SM. Relationships of generalized and regional adiposity to insulin sensitivity in men. J Clin Invest 1995; 96: 88–98. 9 Ross R, Freeman J, Hudson R, Janssen I. Abdominal obesity, muscle composition, and insulin resistance in premenopausal women. J Clin Endocrinol Metab 2002; 87: 5044–5051. 10 Johanson EH, Jansson PA, Lonn L, Matsuzawa Y, Funahashi T, Taskinen MR, Smith U, Axelsen M. Fat distribution, lipid accumulation in the liver, and exercise capacity do not explain the insulin resistance in healthy males with a family history for type 2 diabetes. J Clin Endocrinol Metab 2003; 88: 4232–4238. 11 Salmenniemi U, Ruotsalainen E, Pihlajama¨ki J, Vauhkonen I, Kainulainen S, Punnonen K, Vanninen E, Laakso M. Multiple abnormalities in glucose and energy metabolism and coordinated changes in levels of adiponectin, cytokines, and adhesion molecules in subjects with metabolic syndrome. Circulation 2004; 110: 3842–3848. 12 Alberti KG, Zimmet PZ. Definition, diagnosis and classification of diabetes mellitus and its complications. Part 1: diagnosis and classification of diabetes mellitus provisional report of a WHO consultation. Diabet Med 1998; 15: 539–553. 13 Galvin P, Ward G, Walters J, Pestell R, Koschmann M, Vaag A, Martin I, Best JD, Alford F. A simple method for quantitation of insulin sensitivity and insulin release from an intravenous glucose tolerance test. Diabet Med 1992; 9: 921–928. 14 DeFronzo RA, Tobin JD, Andres R. Glucose clamp technique: a method for quantifying insulin secretion and resistance. Am J Physiol 1979; 237: E214–E223.
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15 Lehto M, Tuomi T, Mahtani MM, Widen E, Forsblom C, ¨ m M, Isomaa B, Lehtovirta M, Hyrkk A, Sarelin L, Gullstro Kanninen T, Orho M, Manley S, Turner RC, Brettin T, Kirby A, Thomas J, Duyk G, Lander E, Taskinen MR, Group L. Characterization of the MODY3 phenotype. Early-onset diabetes caused by an insulin secretion defect. J Clin Invest 1997; 99: 582–591. 16 Ferrannini E. The theoretical bases of indirect calorimetry: a review. Metabolism 1988; 37: 287–301. 17 Fuller NJ, Elia M. Potential use of bioelectrical impedance of the ‘whole body’ and of body segments for the assessment of body composition: comparison with densitometry and anthropometry. Eur J Clin Nutr 1989; 43: 779–791. 18 Chowdhury B, Sjostrom L, Alpsten M, Kostanty J, Kvist H, Lofgren R. A multicompartment body composition technique based on computerized tomography. Int J Obes Relat Metab Disord 1994; 18: 219–234. 19 Hawk PB, Oser BL, Summerson WH. In Practical Physiological Chemistry. Blakiston: Philadelphia; 1947. 20 Allison DB, Heo M, Kaplan N, Martin ER. Sibling-based tests of linkage and association for quantitative traits. Am J Hum Genet 1999; 64: 1754–1763. 21 Misra A, Vikram NK. Clinical and pathophysiological consequences of abdominal adiposity and abdominal adipose tissue depots. Nutrition 2003; 19: 457–466. 22 Ruderman NB, Schneider SH, Berchtold P. The ‘metabolicallyobese,’ normal-weight individual. Am J Clin Nutr 1981; 34: 1617– 1621. 23 LeRoith D. Beta-cell dysfunction and insulin resistance in type 2 diabetes: role of metabolic and genetic abnormalities. Am J Med 2002; 113 (Suppl 6A): 3S–11S. 24 Kelley DE, Mandarino LJ. Fuel selection in human skeletal muscle in insulin resistance: a reexamination. Diabetes 2000; 49: 677–683. 25 Perseghin G. Pathogenesis of obesity and diabetes mellitus: insights provided by indirect calorimetry in humans. Acta Diabetol 2001; 38: 7–21. 26 McGarry JD. Banting lecture 2001: dysregulation of fatty acid metabolism in the etiology of type 2 diabetes. Diabetes 2002; 51: 7–18. 27 Nielsen S, Guo Z, Johnson CM, Hensrud DD, Jensen MD. Splanchnic lipolysis in human obesity. J Clin Invest 2004; 113: 1582–1588. 28 Klein S. The case of visceral fat: argument for the defense. J Clin Invest 2004; 113: 1530–1532. 29 Lafontan M, Berlan M. Do regional differences in adipocyte biology provide new pathophysiological insights? Trends Pharmacol Sci 2003; 24: 276–283.